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Exploiting the Web for Semantic Change Detection

Accepted version
Peer-reviewed

Type

Book chapter

Change log

Authors

Basile, P 
McGillivray, Barbara  ORCID logo  https://orcid.org/0000-0003-3426-8200

Abstract

Detecting significant linguistic shifts in the meaning and usage of words has gained more attention over the last few years. Linguistic shifts are especially prevalent on the Internet, where words’ meaning can change rapidly. In this work, we describe the construction of a large diachronic corpus that relies on the UK Web Archive and we propose a preliminary analysis of semantic change detection exploiting a particular technique called Temporal Random Indexing. Results of the evaluation are promising and give us important insights for further investigations.

Description

Title

Exploiting the Web for Semantic Change Detection

Keywords

4605 Data Management and Data Science, 46 Information and Computing Sciences, Clinical Research, Behavioral and Social Science, Basic Behavioral and Social Science

Is Part Of

Discovery Science. DS 2018

Book type

Publisher

Springer Nature

ISBN

978-3-030-01771-2

Rights

All rights reserved
Sponsorship
Alan Turing Institute (EP/N510129/1)